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MethodsNeurosciencePeer-reviewed journal article

A streamlined CRISPR workflow to introduce mutations and generate isogenic iPSCs for modeling amyotrophic lateral sclerosis

Éric DeneaultiD, Mathilde ChaineauiD, Michaël NicouleauiD, María José Castellanos‐MontieliD, Anna Kristina Franco-FloresiD, Ghazal HaghiiD, Carol X.‐Q. CheniD, Narges AbdianiD, Irina ShlaiferiD, Lenore K. BeiteliD, Thomas M. DurcaniD

PDFDOIPreprint

Abstract

Amyotrophic lateral sclerosis (ALS) represents a complex neurodegenerative disorder with significant genetic heterogeneity. To date, both the genetic etiology and the underlying molecular mechanisms driving this disease remain poorly understood, although in recent years a number of studies have highlighted a number of genetic mutations causative for ALS. With these mutations pointing to potential pathways that may be affected within individuals with ALS, having the ability to generate human neurons and other disease relevant cells containing these mutations becomes even more critical if new therapies are to emerge. Recent developments with the advent of induced pluripotent stem cells (iPSCs) and clustered regularly interspaced short palindromic repeats (CRISPR) gene editing fields gave us the tools to introduce or correct a specific mutation at any site within the genome of an iPSC, and thus model the specific contribution of risk mutations. In this study we describe a rapid and efficient way to either introduce a mutation into a control line, or to correct a mutation, generating an isogenic control line from patient-derived iPSCs with a given mutation. The mutations introduced were the G93A mutation into SOD1 or H517Q into FUS, and the mutation corrected was a patient iPSC line with I114T in SOD1. A combination of small molecules and growth factors were used to guide a stepwise differentiation of the edited cells into motor neurons in order to demonstrate that disease-relevant cells could be generated for downstream applications. Through a combination of iPSCs and CRISPR editing, the cells generated here will provide fundamental insights into the molecular mechanisms underlying neuron degeneration in ALS.

Citations
53
FWCI
4.54
Field percentile
top 4%

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